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Moved more to Map library

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This commit is contained in:
Mike Phares
2022-08-29 08:45:01 -07:00
parent 674555b4fc
commit c1d30b5bbc
46 changed files with 1631 additions and 697 deletions
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69
Instance/DlibDotNet.cs
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@ -234,6 +234,7 @@ public class DlibDotNet
sourceDirectoryNames = Array.Empty<string>();
else
{
string? century;
string argZero = Path.GetFullPath(args[0]);
sourceDirectoryNames = argZero.Split(Path.DirectorySeparatorChar);
if (!argZero.StartsWith(propertyConfiguration.RootDirectory))
@ -243,7 +244,8 @@ public class DlibDotNet
if (!configuration.MixedYearRelativePaths.Contains(sourceDirectoryNames[0]))
{
string[] segments = sourceDirectoryNames[0].Split(' ');
if (segments.Length < 2 || segments[^1].Length != 4 || (segments[^1][..2] != "19" && segments[^1][..2] != "20"))
century = segments[^1].Length == 4 ? segments[^1][..2] : null;
if (segments.Length < 2 || century is null || (century != "18" && century != "19" && century != "20"))
throw new Exception("root subdirectory must have a year at the end or directory name needs to be added to the exclude list!");
}
}
@ -362,7 +364,7 @@ public class DlibDotNet
string message = $"{container.R:000}.{container.G} / {containersCount:000}) {filteredItems.Length:000} file(s) - {totalSeconds} total second(s) - {outputResolution} - {container.SourceDirectory}";
using (ProgressBar progressBar = new(filteredItems.Length, message, options))
{
_ = Parallel.For(0, filteredItems.Length, parallelOptions, i =>
_ = Parallel.For(0, filteredItems.Length, parallelOptions, (i, state) =>
{
try
{
@ -640,6 +642,36 @@ public class DlibDotNet
}
}
private static List<(string, int, Mapping, DateTime, bool?, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>)> Convert(Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> keyValuePairs)
{
List<(string, int, Mapping, DateTime, bool?, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>)> results = new();
MappingContainer mc;
foreach (KeyValuePair<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> keyValuePair in keyValuePairs)
{
foreach ((FaceRecognitionDotNet.FaceEncoding _, MappingContainer mappingContainer) in keyValuePair.Value)
{
mc = mappingContainer;
results.Add(new(mc.Key, mc.Id, mc.Mapping, mc.MinimumDateTime, mc.IsWrongYear, keyValuePair.Value));
}
}
return results;
}
private static Dictionary<int, List<MappingContainer>> Strip(Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> keyValuePairs)
{
Dictionary<int, List<MappingContainer>> results = new();
foreach (KeyValuePair<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> keyValuePair in keyValuePairs)
{
foreach ((FaceRecognitionDotNet.FaceEncoding _, MappingContainer mappingContainer) in keyValuePair.Value)
{
if (!results.ContainsKey(mappingContainer.Id))
results.Add(mappingContainer.Id, new());
results[mappingContainer.Id].Add(mappingContainer);
}
}
return results;
}
private void Search(Property.Models.Configuration configuration, bool reverse, Model? model, PredictorModel? predictorModel, string argZero, Person[] people, bool isSilent)
{
if (_Log is null)
@ -653,8 +685,8 @@ public class DlibDotNet
string eResultsFullGroupDirectory;
string zResultsFullGroupDirectory;
string d2ResultsFullGroupDirectory;
Dictionary<string, List<Person>> peopleCollection = A2_People.Convert(people);
Map.Models.MapLogic mapLogic = new(_AppSettings.MaxDegreeOfParallelism, _Configuration.PropertyConfiguration);
Dictionary<string, Person> personKeyValuePairs = A2_People.Convert(people);
Map.Models.MapLogic mapLogic = new(_AppSettings.MaxDegreeOfParallelism, _Configuration.PropertyConfiguration, _Resize.FilenameExtension, personKeyValuePairs);
A_Property propertyLogic = new(_AppSettings.MaxDegreeOfParallelism, _Configuration.PropertyConfiguration, _Resize.FilenameExtension, reverse, model, predictorModel, mapLogic.IndicesFromNew, mapLogic.KeyValuePairs);
if (string.IsNullOrEmpty(configuration.RootDirectory))
containers = A_Property.Get(configuration, propertyLogic);
@ -669,30 +701,35 @@ public class DlibDotNet
mapLogic.UseKeyValuePairsSaveFaceEncoding(containers);
foreach (Container container in containers)
{
mapLogic.AddToNamed(container.Items);
mapLogic.AddToMapping(container.Items);
if (_Configuration.SaveShortcutsForOutputResolutions.Contains(outputResolution))
D_Face.SaveShortcuts(_Configuration.JuliePhares, dResultsFullGroupDirectory, ticks, peopleCollection, mapLogic, container.Items);
mapLogic.SaveShortcuts(_Configuration.JuliePhares, dResultsFullGroupDirectory, ticks, container.Items);
}
mapLogic.SaveAllCollection();
if (_Configuration.SaveResizedSubfiles)
{
string dFacesContentDirectory;
string eDistanceContentDirectory;
string eDistanceCollectionDirectory;
string zPropertyHolderContentDirectory;
string zPropertyHolderSingletonDirectory;
string zPropertyHolderCollectionDirectory;
dFacesContentDirectory = Path.Combine(dResultsFullGroupDirectory, "()");
eDistanceContentDirectory = Path.Combine(eResultsFullGroupDirectory, $"({ticks})");
zPropertyHolderSingletonDirectory = Path.Combine(zResultsFullGroupDirectory, "{}");
eDistanceCollectionDirectory = Path.Combine(eResultsFullGroupDirectory, $"[{ticks}]");
List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> collection;
collection = E_Distance.ParallelWork(_AppSettings.MaxDegreeOfParallelism, argZero, mapLogic, containers);
zPropertyHolderContentDirectory = Path.Combine(zResultsFullGroupDirectory, $"({ticks})");
zPropertyHolderCollectionDirectory = Path.Combine(zResultsFullGroupDirectory, $"[{ticks}]");
Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> keyValuePairs = _Distance.ParallelWork(_AppSettings.MaxDegreeOfParallelism, _Configuration.IgnoreRelativePaths, argZero, ticks, containers);
_ = LogDeltaInSeconds(ticks, nameof(E_Distance.ParallelWork));
Dictionary<int, List<MappingContainer>> strippedKeyValuePairs = Strip(keyValuePairs);
List<(string, int, Mapping, DateTime, bool?, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>)> collection = Convert(keyValuePairs);
mapLogic.SaveMapping(argZero, containers, dFacesContentDirectory, d2ResultsFullGroupDirectory, zPropertyHolderContentDirectory);
_ = LogDeltaInMinutes(ticks, nameof(mapLogic.SaveMapping));
_Distance.AddToFaceDistance(_AppSettings.MaxDegreeOfParallelism, argZero, ticks, mapLogic, containers, outputResolution, collection);
_ = LogDeltaInSeconds(ticks, nameof(_Distance.AddToFaceDistance));
mapLogic.AddToClosest(_AppSettings.MaxDegreeOfParallelism, argZero, containers);
_ = LogDeltaInMinutes(ticks, nameof(mapLogic.AddToClosest));
mapLogic.SaveClosest(argZero, containers, dFacesContentDirectory, d2ResultsFullGroupDirectory, zPropertyHolderContentDirectory);
_ = LogDeltaInMinutes(ticks, nameof(mapLogic.SaveClosest));
E_Distance.SavePropertyHolders(argZero, containers, zPropertyHolderSingletonDirectory);
_ = LogDeltaInSeconds(ticks, nameof(E_Distance.SavePropertyHolders));
E_Distance.SaveThreeSigmaFaceEncodings(collection, peopleCollection, eDistanceCollectionDirectory);
_ = LogDeltaInSeconds(ticks, nameof(E_Distance.SaveThreeSigmaFaceEncodings));
E_Distance.SaveClosest(argZero, containers, peopleCollection, dFacesContentDirectory, d2ResultsFullGroupDirectory, eDistanceContentDirectory);
_ = LogDeltaInMinutes(ticks, nameof(E_Distance.SaveClosest));
}
if (!_Configuration.LoadOrCreateThenSaveImageFacesResultsForOutputResolutions.Any())
break;

10
Instance/Models/_A2_People.cs
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@ -73,16 +73,16 @@ internal class A2_People
return results.ToArray();
}
internal static Dictionary<string, List<Person>> Convert(Person[] people)
internal static Dictionary<string, Person> Convert(Person[] people)
{
Dictionary<string, List<Person>> results = new();
Dictionary<string, Person> results = new();
string personKey;
foreach (Person person in people)
{
personKey = Shared.Models.Stateless.Methods.IPersonBirthday.GetFormatted(person.Birthday);
if (!results.ContainsKey(personKey))
results.Add(personKey, new List<Person>());
results[personKey].Add(person);
if (results.ContainsKey(personKey))
break;
results.Add(personKey, person);
}
return results;
}

2
Instance/Models/_D2_FaceParts.cs
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@ -153,7 +153,7 @@ internal class D2_FaceParts
collection.Add(new(face, string.Empty, string.Empty));
continue;
}
deterministicHashCodeKey = Shared.Models.Stateless.Methods.INamed.GetDeterministicHashCodeKey(item, face);
deterministicHashCodeKey = Shared.Models.Stateless.Methods.IMapping.GetDeterministicHashCodeKey(item, face);
fileInfo = new FileInfo(Path.Combine(facesDirectory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}{_FilenameExtension}"));
if (!fileInfo.Exists)
{

58
Instance/Models/_D_Face.cs
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@ -2,14 +2,12 @@ using System.Drawing;
using System.Drawing.Drawing2D;
using System.Drawing.Imaging;
using System.Text.Json;
using System.Text.RegularExpressions;
using View_by_Distance.FaceRecognitionDotNet;
using View_by_Distance.Metadata.Models;
using View_by_Distance.Property.Models;
using View_by_Distance.Resize.Models;
using View_by_Distance.Shared.Models;
using View_by_Distance.Shared.Models.Stateless;
using WindowsShortcutFactory;
namespace View_by_Distance.Instance.Models;
@ -346,7 +344,7 @@ public class D_Face
collection.Add(new(face, string.Empty));
continue;
}
deterministicHashCodeKey = Shared.Models.Stateless.Methods.INamed.GetDeterministicHashCodeKey(item, face);
deterministicHashCodeKey = Shared.Models.Stateless.Methods.IMapping.GetDeterministicHashCodeKey(item, face);
fileInfo = new FileInfo(Path.Combine(facesDirectory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}{_FilenameExtension}"));
if (!fileInfo.Exists)
{
@ -368,60 +366,6 @@ public class D_Face
SaveFaces(item.ResizedFileHolder, collection);
}
internal static void SaveShortcuts(string[] juliePhares, string dResultsFullGroupDirectory, long ticks, Dictionary<string, List<Person>> peopleCollection, Map.Models.MapLogic mapLogic, List<Item> items)
{
Person person;
string fileName;
string fullName;
DateTime? minimumDateTime;
WindowsShortcut windowsShortcut;
const string pattern = @"[\\,\/,\:,\*,\?,\"",\<,\>,\|]";
string dFacesContentDirectory = Path.Combine(dResultsFullGroupDirectory, $"({ticks})");
List<(Item, (string, Face?, (string, string, string, string))[])> collections = mapLogic.GetCollection(items, dFacesContentDirectory);
foreach ((Item item, (string personKey, Face? _, (string, string, string, string))[] collection) in collections)
{
if (collection.Length != 1)
continue;
foreach ((string personKey, Face? _, (string directory, string copyDirectory, string copyFileName, string shortcutFileName)) in collection)
{
if (string.IsNullOrEmpty(personKey))
continue;
if (item.Property?.Id is null || item.ImageFileHolder is null || item.ResizedFileHolder is null)
continue;
minimumDateTime = Shared.Models.Stateless.Methods.IProperty.GetMinimumDateTime(item.Property);
if (minimumDateTime is null)
continue;
if (!Directory.Exists(directory))
{
_ = Directory.CreateDirectory(directory);
if (!string.IsNullOrEmpty(personKey) && peopleCollection.ContainsKey(personKey))
{
person = peopleCollection[personKey][0];
fullName = string.Concat(Regex.Replace(Shared.Models.Stateless.Methods.IPersonName.GetFullName(person.Name), pattern, string.Empty), ".txt");
File.WriteAllText(Path.Combine(directory, fullName), string.Empty);
}
}
if (juliePhares.Contains(personKey) && !string.IsNullOrEmpty(copyDirectory))
{
if (!Directory.Exists(copyDirectory))
_ = Directory.CreateDirectory(copyDirectory);
fileName = Path.Combine(copyDirectory, $"{item.Property.Id.Value}{item.ResizedFileHolder.ExtensionLowered}");
if (!File.Exists(fileName))
File.Copy(item.ResizedFileHolder.FullName, fileName);
}
fileName = Path.Combine(directory, $"{item.Property.Id.Value}.lnk");
if (File.Exists(fileName))
continue;
windowsShortcut = new() { Path = item.ImageFileHolder.FullName };
windowsShortcut.Save(fileName);
windowsShortcut.Dispose();
if (!File.Exists(fileName))
continue;
File.SetLastWriteTime(fileName, minimumDateTime.Value);
}
}
}
private static bool HasLeftAndRight(Dictionary<string, FacePoint[]> faceParts)
{
bool result = true;

520
Instance/Models/_E_Distance.cs
View File

@ -1,13 +1,10 @@
using System.Text.Json;
using System.Text.RegularExpressions;
using View_by_Distance.FaceRecognitionDotNet;
using View_by_Distance.Metadata.Models;
using View_by_Distance.Property.Models;
using View_by_Distance.Resize.Models;
using View_by_Distance.Shared.Models;
using View_by_Distance.Shared.Models.Properties;
using View_by_Distance.Shared.Models.Stateless;
using WindowsShortcutFactory;
namespace View_by_Distance.Instance.Models;
@ -424,6 +421,152 @@ internal class E_Distance
return result;
}
private static int GetSelectedIndex(int maxDegreeOfParallelism, Random random, List<FaceRecognitionDotNet.FaceEncoding> faceEncodings)
{
int? result;
int selectedIndex;
List<(int? Index, double? Sum)> faceDistanceCollections = new();
if (maxDegreeOfParallelism == 1)
{
double sum;
List<double> faceDistances;
for (int i = 0; i < faceEncodings.Count; i++)
{
faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncodings[i]);
sum = faceDistances.Sum();
faceDistanceCollections.Add(new(i, sum));
}
}
else
{
for (int i = 0; i < faceEncodings.Count; i++)
faceDistanceCollections.Add(new(null, null));
ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
_ = Parallel.For(0, faceEncodings.Count, parallelOptions, (i, state) =>
{
List<double> faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncodings[i]);
double sum = faceDistances.Sum();
lock (faceDistanceCollections)
faceDistanceCollections[i] = new(i, sum);
});
}
faceDistanceCollections = faceDistanceCollections.OrderBy(l => l.Sum).ToList();
if (faceDistanceCollections.Count != faceEncodings.Count)
throw new Exception();
if (faceDistanceCollections.Count > 1000)
selectedIndex = random.Next(0, 36);
else if (faceDistanceCollections.Count > 500)
selectedIndex = random.Next(0, 31);
else if (faceDistanceCollections.Count > 200)
selectedIndex = random.Next(0, 26);
else if (faceDistanceCollections.Count > 100)
selectedIndex = random.Next(0, 21);
else if (faceDistanceCollections.Count > 50)
selectedIndex = random.Next(0, 16);
else if (faceDistanceCollections.Count > 25)
selectedIndex = random.Next(0, 11);
else if (faceDistanceCollections.Count > 10)
selectedIndex = random.Next(0, 6);
else if (faceDistanceCollections.Count > 5)
selectedIndex = random.Next(0, 3);
else
selectedIndex = 0;
result = faceDistanceCollections[selectedIndex].Index;
if (result is null)
throw new NullReferenceException(nameof(result));
return result.Value;
}
private static void SetFiltered(List<(FaceRecognitionDotNet.FaceEncoding FaceEncoding, MappingContainer MappingContainer)> collection)
{
double ucl;
bool check;
double average;
double[] doubles;
double standardDeviation;
double?[] nullableDoubles;
for (int i = 0; i < int.MaxValue; i++)
{
check = true;
nullableDoubles = (from l in collection where l.MappingContainer.Mapping.Filtered is not null && !l.MappingContainer.Mapping.Filtered.Value select l.MappingContainer.Distance).ToArray();
doubles = (from l in nullableDoubles where l.HasValue select l.Value).ToArray();
if (doubles.Length < 4)
break;
average = doubles.Average();
standardDeviation = GetStandardDeviation(doubles, average);
ucl = average + (standardDeviation * 3);
if (ucl > IFaceDistance.Tolerance)
ucl = IFaceDistance.Tolerance;
foreach ((FaceRecognitionDotNet.FaceEncoding _, MappingContainer mappingContainer) in collection)
{
if (mappingContainer.Mapping.Filtered is null || mappingContainer.Mapping.Filtered.Value || mappingContainer.Distance <= ucl)
continue;
if (check)
check = false;
mappingContainer.Mapping.SetFiltered();
}
if (check)
break;
}
}
private static FaceDistance GetFaceDistanceParallelFor(Face face, FaceRecognitionDotNet.FaceEncoding faceEncoding, Mapping mapping, DateTime minimumDateTime, bool? isWrongYear, string key, FaceRecognitionDotNet.FaceEncoding[] faceEncodings)
{
FaceDistance result;
if (face.Location?.NormalizedPixelPercentage is null)
throw new NullReferenceException(nameof(face.Location.NormalizedPixelPercentage));
List<double> faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncoding);
result = new(faceDistances, isWrongYear, key, mapping, minimumDateTime);
return result;
}
private static List<FaceDistance> GetFaceDistanceCollection(int maxDegreeOfParallelism, List<(string Key, int Id, Mapping Mapping, DateTime MinimumDateTime, bool? IsWrongYear, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>)> collection, Face face)
{
List<FaceDistance> results;
if (face.FaceEncoding is null)
throw new NullReferenceException(nameof(face.FaceEncoding));
FaceRecognitionDotNet.FaceEncoding faceEncoding = FaceRecognition.LoadFaceEncoding(face.FaceEncoding.RawEncoding);
if (maxDegreeOfParallelism == 1)
{
results = new();
FaceDistance faceDistance;
List<double> faceDistances;
FaceRecognitionDotNet.FaceEncoding[] faceEncodings;
if (face.Location?.NormalizedPixelPercentage is null)
throw new NullReferenceException(nameof(face.Location.NormalizedPixelPercentage));
foreach ((string key, int id, Mapping mapping, DateTime minimumDateTime, bool? isWrongYear, List<(FaceRecognitionDotNet.FaceEncoding FaceEncoding, MappingContainer _)> faceEncodingContainers) in collection)
{
faceEncodings = (from l in faceEncodingContainers select l.FaceEncoding).ToArray();
faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncoding);
faceDistance = new(faceDistances, isWrongYear, key, mapping, minimumDateTime);
results.Add(faceDistance);
if (results.Count > IFaceDistance.MaximumPer)
break;
}
}
else
{
results = new();
ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
_ = Parallel.For(0, collection.Count, parallelOptions, (i, state) =>
{
(string key, int id, Mapping mapping, DateTime minimumDateTime, bool? isWrongYear, List<(FaceRecognitionDotNet.FaceEncoding FaceEncoding, MappingContainer _)> faceEncodingContainers) = collection[i];
FaceRecognitionDotNet.FaceEncoding[] faceEncodings = (from l in faceEncodingContainers select l.FaceEncoding).ToArray();
FaceDistance? closest = GetFaceDistanceParallelFor(face, faceEncoding, mapping, minimumDateTime, isWrongYear, key, faceEncodings);
if (closest is not null)
{
lock (results)
{
results.Add(closest);
if (results.Count > IFaceDistance.MaximumPer)
state.Break();
}
}
});
}
return results;
}
private static FaceRecognitionDotNet.FaceEncoding? GetFaceEncoding(Face face)
{
FaceRecognitionDotNet.FaceEncoding? result;
@ -434,24 +577,18 @@ internal class E_Distance
return result;
}
private static (int index, double sum) GetIndexAndSum(int i, List<FaceRecognitionDotNet.FaceEncoding> results)
{
List<double> faceDistances = FaceRecognition.FaceDistances(results, results[i]);
return new(i, faceDistances.Sum());
}
private static List<FaceRecognitionDotNet.FaceEncoding> GetFaceEncodings(int maxDegreeOfParallelism, List<(DateTime MinimumDateTime, bool? IsWrongYear, PersonBirthday PersonBirthday, Face Face)> collection)
private static List<FaceRecognitionDotNet.FaceEncoding> GetFaceEncodingsOnly(int maxDegreeOfParallelism, List<MappingContainer> collection)
{
List<FaceRecognitionDotNet.FaceEncoding> results;
if (maxDegreeOfParallelism == 1)
{
results = new();
FaceRecognitionDotNet.FaceEncoding faceEncoding;
foreach ((DateTime _, bool? _, PersonBirthday _, Face face) in collection)
foreach (MappingContainer mappingContainer in collection)
{
if (face.FaceEncoding is null || face.Location?.NormalizedPixelPercentage is null)
if (mappingContainer.Face?.FaceEncoding is null || mappingContainer.Face.Location?.NormalizedPixelPercentage is null)
continue;
faceEncoding = FaceRecognition.LoadFaceEncoding(face.FaceEncoding.RawEncoding);
faceEncoding = FaceRecognition.LoadFaceEncoding(mappingContainer.Face.FaceEncoding.RawEncoding);
results.Add(faceEncoding);
}
}
@ -459,9 +596,12 @@ internal class E_Distance
{
results = new();
ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
_ = Parallel.For(0, collection.Count, parallelOptions, i =>
_ = Parallel.For(0, collection.Count, parallelOptions, (i, state) =>
{
FaceRecognitionDotNet.FaceEncoding? faceEncoding = GetFaceEncoding(collection[i].Face);
Face? face = collection[i].Face;
if (face is null)
throw new Exception();
FaceRecognitionDotNet.FaceEncoding? faceEncoding = GetFaceEncoding(face);
if (faceEncoding is not null)
{
lock (results)
@ -469,136 +609,68 @@ internal class E_Distance
}
});
}
if (collection.Count == results.Count && results.Count > 1)
{
double sum;
int lowestIndex;
double lowestSum;
List<double> faceDistances;
if (maxDegreeOfParallelism == 1)
{
lowestIndex = 0;
lowestSum = double.MaxValue;
for (int i = 0; i < results.Count; i++)
{
faceDistances = FaceRecognition.FaceDistances(results, results[i]);
sum = faceDistances.Sum();
if (sum >= lowestSum)
continue;
lowestIndex = i;
lowestSum = sum;
}
}
else
{
List<(int Index, double Sum)> indicesAndSums = new();
ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
_ = Parallel.For(0, results.Count, parallelOptions, i =>
{
(int index, double sum) = GetIndexAndSum(i, results);
lock (indicesAndSums)
indicesAndSums.Add(new(index, sum));
});
(lowestIndex, lowestSum) = (from l in indicesAndSums orderby l.Sum select l).First();
}
faceDistances = FaceRecognition.FaceDistances(results, results[lowestIndex]);
sum = faceDistances.Sum();
if (sum == lowestSum)
{
double average = faceDistances.Average();
double standardDeviation = GetStandardDeviation(faceDistances, average);
double lcl = average - (standardDeviation * 3);
double ucl = average + (standardDeviation * 3);
for (int i = results.Count - 1; i > -1; i--)
{
if (faceDistances[i] < lcl || faceDistances[i] > ucl)
results.RemoveAt(i);
}
}
}
return results;
}
private static List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> GetThreeSigmaFaceEncodings(int maxDegreeOfParallelism, Dictionary<string, List<(DateTime, bool?, PersonBirthday, Face)>> keyValuePairs)
private Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> GetThreeSigmaFaceEncodings(int maxDegreeOfParallelism, long ticks, Dictionary<string, List<MappingContainer>> keyValuePairs)
{
List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> results = new();
const int zero = 0;
if (_Log is null)
throw new NullReferenceException(nameof(_Log));
Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> results = new();
int totalSeconds;
int selectedIndex;
Random random = new();
List<double> faceDistances;
MappingContainer mappingContainer;
int keyValuePairsCount = keyValuePairs.Count;
FaceRecognitionDotNet.FaceEncoding faceEncoding;
List<FaceRecognitionDotNet.FaceEncoding> faceEncodings;
foreach (KeyValuePair<string, List<(DateTime MinimumDateTime, bool? IsWrongYear, PersonBirthday PersonBirthday, Face _)>> keyValuePair in keyValuePairs)
List<(FaceRecognitionDotNet.FaceEncoding FaceEncoding, MappingContainer MappingContainer)> collection;
foreach (KeyValuePair<string, List<MappingContainer>> keyValuePair in keyValuePairs)
{
faceEncodings = GetFaceEncodings(maxDegreeOfParallelism, keyValuePair.Value);
results.Add(new(keyValuePair.Value[zero].MinimumDateTime, keyValuePair.Value[zero].IsWrongYear, keyValuePair.Value[zero].PersonBirthday, faceEncodings.ToArray()));
}
return results;
}
private static Closest? GetClosestParallelFor(DateTime minimumDateTime, bool? isWrongYear, Face face, FaceRecognitionDotNet.FaceEncoding faceEncoding, (DateTime MinimumDateTime, bool? IsWrongYear, PersonBirthday PersonBirthday, FaceRecognitionDotNet.FaceEncoding[] FaceEncodings) tuple)
{
Closest? result;
if (isWrongYear.HasValue && !isWrongYear.Value && minimumDateTime < tuple.PersonBirthday.Value)
result = null;
else
{
List<double> faceDistances = FaceRecognition.FaceDistances(tuple.FaceEncodings, faceEncoding);
result = new(face.Location?.NormalizedPixelPercentage, tuple.MinimumDateTime, tuple.IsWrongYear, tuple.PersonBirthday, faceDistances);
if (result.Minimum > Shared.Models.Stateless.IClosest.MaximumMinimum)
result = null;
}
return result;
}
private static Closest[] GetClosestCollection(int maxDegreeOfParallelism, List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> collection, DateTime itemMinimumDateTime, bool? itemIsWrongYear, Face face)
{
Closest[] results;
List<Closest> closestCollection;
if (face.FaceEncoding is null)
throw new NullReferenceException(nameof(face.FaceEncoding));
FaceRecognitionDotNet.FaceEncoding faceEncoding = FaceRecognition.LoadFaceEncoding(face.FaceEncoding.RawEncoding);
if (maxDegreeOfParallelism == 1)
{
closestCollection = new();
Closest closest;
List<double> faceDistances;
foreach ((DateTime minimumDateTime, bool? isWrongYear, PersonBirthday personBirthday, FaceRecognitionDotNet.FaceEncoding[] faceEncodings) in collection)
collection = new();
faceEncodings = GetFaceEncodingsOnly(maxDegreeOfParallelism, keyValuePair.Value);
for (int i = 0; i < faceEncodings.Count; i++)
{
if (itemIsWrongYear.HasValue && !itemIsWrongYear.Value && itemMinimumDateTime < personBirthday.Value)
continue;
faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncoding);
closest = new(face.Location?.NormalizedPixelPercentage, minimumDateTime, isWrongYear, personBirthday, faceDistances);
if (closest.Minimum > Shared.Models.Stateless.IClosest.MaximumMinimum)
continue;
closestCollection.Add(closest);
faceEncoding = faceEncodings[i];
mappingContainer = keyValuePair.Value[i];
collection.Add(new(faceEncoding, mappingContainer));
}
results.Add(keyValuePair.Key, collection);
if (faceEncodings.Count == 1)
selectedIndex = 0;
else
selectedIndex = GetSelectedIndex(maxDegreeOfParallelism, random, faceEncodings);
faceDistances = FaceRecognition.FaceDistances(faceEncodings, faceEncodings[selectedIndex]);
for (int i = 0; i < faceEncodings.Count; i++)
collection[i].MappingContainer.SetDistance(faceDistances[i]);
if (collection.Count > 1)
SetFiltered(collection);
totalSeconds = (int)Math.Floor(new TimeSpan(DateTime.Now.Ticks - ticks).TotalSeconds);
_Log.Information($"{keyValuePairsCount:0000}) {totalSeconds} total second(s) - {keyValuePair.Key} - {collection[selectedIndex].MappingContainer.Mapping.DisplayDirectoryName}");
}
else
{
closestCollection = new();
ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
_ = Parallel.For(0, collection.Count, parallelOptions, i =>
{
Closest? closest = GetClosestParallelFor(itemMinimumDateTime, itemIsWrongYear, face, faceEncoding, collection[i]);
if (closest is not null)
{
lock (closestCollection)
closestCollection.Add(closest);
}
});
}
results = Shared.Models.Stateless.Methods.IClosest.Get(closestCollection);
return results;
}
private static void AddClosest(int maxDegreeOfParallelism, string argZero, Map.Models.MapLogic mapLogic, List<Container> containers, List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> collection)
internal Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> ParallelWork(int maxDegreeOfParallelism, string[] ignoreRelativePaths, string argZero, long ticks, List<Container> containers)
{
string key;
Dictionary<string, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>> results;
Dictionary<string, List<MappingContainer>> keyValuePairs = Map.Models.Stateless.IMapLogic.GetKeyValuePairs(ignoreRelativePaths, argZero, containers);
results = GetThreeSigmaFaceEncodings(maxDegreeOfParallelism, ticks, keyValuePairs);
return results;
}
public void AddToFaceDistance(int maxDegreeOfParallelism, string argZero, long ticks, Map.Models.MapLogic mapLogic, List<Container> containers, string outputResolution, List<(string, int, Mapping, DateTime, bool?, List<(FaceRecognitionDotNet.FaceEncoding, MappingContainer)>)> collection)
{
if (_Log is null)
throw new NullReferenceException(nameof(_Log));
Face face;
Closest closest;
string personKey;
bool? itemIsWrongYear;
Closest[] closestCollection;
DateTime? itemMinimumDateTime;
string message;
int totalSeconds;
double deterministicHashCodeKey;
Dictionary<string, int> results = new();
DateTime dateTime = DateTime.Now;
List<FaceDistance> faceDistances;
int containersCount = containers.Count;
foreach (Container container in containers)
{
if (!container.Items.Any())
@ -607,55 +679,29 @@ internal class E_Distance
continue;
foreach (Item item in container.Items)
{
if (item.ImageFileHolder is null || item.Property is null || item.Named.Any())
if (item.ImageFileHolder is null || item.Property?.Id is null)
continue;
itemMinimumDateTime = Shared.Models.Stateless.Methods.IProperty.GetMinimumDateTime(item.Property);
if (itemMinimumDateTime is null)
continue;
(itemIsWrongYear, _) = Map.Models.MapLogic.IsWrongYear(item);
if (Shared.Models.Stateless.IClosest.SkipIsWrongYear && itemIsWrongYear.HasValue && itemIsWrongYear.Value)
continue;
item.Closest.Clear();
for (int i = 0; i < item.Faces.Count; i++)
{
face = item.Faces[i];
closest = new(face.Location?.NormalizedPixelPercentage, itemMinimumDateTime.Value, itemIsWrongYear);
item.Closest.Add(closest);
face.FaceDistances.Clear();
if (face.FaceEncoding is null || face.Location?.NormalizedPixelPercentage is null)
continue;
deterministicHashCodeKey = Shared.Models.Stateless.Methods.INamed.GetDeterministicHashCodeKey(item, face);
closestCollection = GetClosestCollection(maxDegreeOfParallelism, collection, itemMinimumDateTime.Value, itemIsWrongYear, face);
for (int j = 0; j < closestCollection.Length; j++)
{
closest = closestCollection[j];
if (closest.PersonBirthday is null)
continue;
personKey = Shared.Models.Stateless.Methods.IPersonBirthday.GetFormatted(closest.PersonBirthday);
if (mapLogic.IsIncorrect(deterministicHashCodeKey, personKey))
continue;
key = Map.Models.MapLogic.GetKey(closest.MinimumDateTime, closest.IsWrongYear, closest.PersonBirthday);
if (!results.ContainsKey(key))
results.Add(key, 0);
else if (results[key] > Shared.Models.Stateless.IClosest.MaximumPer)
continue;
results[key] += 1;
item.Closest[0] = closest;
break;
}
if ((from l in item.Mapping where l.NormalizedPixelPercentage.HasValue && l.NormalizedPixelPercentage.Value == face.Location.NormalizedPixelPercentage.Value select true).Any())
continue;
deterministicHashCodeKey = Shared.Models.Stateless.Methods.IMapping.GetDeterministicHashCodeKey(item, face);
if (mapLogic.Skip(deterministicHashCodeKey))
continue;
faceDistances = GetFaceDistanceCollection(maxDegreeOfParallelism, collection, face);
face.FaceDistances.AddRange(faceDistances);
}
}
totalSeconds = (int)Math.Floor(new TimeSpan(DateTime.Now.Ticks - ticks).TotalSeconds);
message = $"{container.R:000}.{container.G} / {containersCount:000}) {container.Items.Count:000} file(s) - {totalSeconds} total second(s) - {outputResolution} - {container.SourceDirectory}";
_Log.Information(message);
}
}
internal static List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> ParallelWork(int maxDegreeOfParallelism, string argZero, Map.Models.MapLogic mapLogic, List<Container> containers)
{
List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> results;
Dictionary<string, List<(DateTime, bool?, PersonBirthday, Face)>> keyValuePairs = Map.Models.MapLogic.GetKeyValuePairs(argZero, containers);
results = GetThreeSigmaFaceEncodings(maxDegreeOfParallelism, keyValuePairs);
AddClosest(maxDegreeOfParallelism, argZero, mapLogic, containers, results);
return results;
}
public static void SavePropertyHolders(string argZero, List<Container> containers, string zPropertyHolderSingletonDirectory)
{
string json;
@ -672,8 +718,6 @@ internal class E_Distance
{
if (item.ImageFileHolder is null || item.Property is null || !item.Faces.Any() || !item.Closest.Any())
continue;
if (!(from l in item.Closest where l.Average.HasValue select true).Any())
continue;
json = JsonSerializer.Serialize(item, jsonSerializerOptions);
fileInfo = new(string.Concat(zPropertyHolderSingletonDirectory, item.RelativePath, ".json"));
if (fileInfo.Directory is null)
@ -685,140 +729,4 @@ internal class E_Distance
}
}
internal static void SaveThreeSigmaFaceEncodings(List<(DateTime, bool?, PersonBirthday, FaceRecognitionDotNet.FaceEncoding[])> collection, Dictionary<string, List<Person>> peopleCollection, string eDistanceCollectionDirectory)
{
string json;
string checkFile;
string personKey;
string directory;
List<double[]> rawEncodings;
Person person;
const string facePopulatedKey = "ThreeSigma";
const string pattern = @"[\\,\/,\:,\*,\?,\"",\<,\>,\|]";
foreach ((DateTime minimumDateTime, bool? isWrongYear, PersonBirthday personBirthday, FaceRecognitionDotNet.FaceEncoding[] faceEncodings) in collection)
{
rawEncodings = new();
checkFile = string.Empty;
personKey = Shared.Models.Stateless.Methods.IPersonBirthday.GetFormatted(personBirthday);
directory = Map.Models.MapLogic.GetDirectory(eDistanceCollectionDirectory, facePopulatedKey, minimumDateTime, isWrongYear, personBirthday, personKey);
if (!peopleCollection.ContainsKey(personKey))
continue;
person = peopleCollection[personKey][0];
checkFile = string.Concat(directory, " - ", Regex.Replace(Shared.Models.Stateless.Methods.IPersonName.GetFullName(person.Name), pattern, string.Empty), ".json");
if (string.IsNullOrEmpty(checkFile))
continue;
if (!Directory.Exists(directory))
_ = Directory.CreateDirectory(directory);
for (int i = 0; i < faceEncodings.Length; i++)
rawEncodings.Add(faceEncodings[i].GetRawEncoding());
json = JsonSerializer.Serialize(rawEncodings, new JsonSerializerOptions { WriteIndented = true });
_ = Shared.Models.Stateless.Methods.IPath.WriteAllText(checkFile, json, updateDateWhenMatches: true, compareBeforeWrite: true);
}
}
internal static List<(IFileHolder? resizedFileHolder, string directory, FileInfo? faceFileInfo, string checkFile, string shortcutFile)> GetClosest(string argZero, List<Container> containers, Dictionary<string, List<Person>> peopleCollection, string dFacesContentDirectory, string d2ResultsFullGroupDirectory, string eDistanceContentDirectory)
{
List<(IFileHolder?, string, FileInfo?, string, string)> results = new();
Person person;
string checkFile;
string directory;
string personKey;
string personName;
string shortcutFile;
FileInfo faceFileInfo;
string? directoryName;
string facesDirectory;
string personDirectory;
FileInfo landmarkFileInfo;
string landmarksDirectory;
double deterministicHashCodeKey;
const string facePopulatedKey = nameof(Closest);
const string pattern = @"[\\,\/,\:,\*,\?,\"",\<,\>,\|]";
foreach (Container container in containers)
{
if (!container.Items.Any())
continue;
if (!container.SourceDirectory.StartsWith(argZero))
continue;
foreach (Item item in container.Items)
{
if (item.ImageFileHolder is null || item.Property?.Id is null || item.ResizedFileHolder is null || item.Named.Any())
continue;
if (!item.Closest.Any())
continue;
directoryName = Path.GetDirectoryName(item.RelativePath);
if (directoryName is null)
throw new Exception();
foreach (Closest closest in item.Closest)
{
if (closest.Average is null || closest.NormalizedPixelPercentage is null || closest.PersonBirthday is null)
continue;
personKey = Shared.Models.Stateless.Methods.IPersonBirthday.GetFormatted(closest.PersonBirthday);
directory = Map.Models.MapLogic.GetDirectory(eDistanceContentDirectory, facePopulatedKey, closest.MinimumDateTime, closest.IsWrongYear, closest.PersonBirthday, personKey);
if (!peopleCollection.ContainsKey(personKey))
personDirectory = string.Empty;
else
{
person = peopleCollection[personKey][0];
personName = Shared.Models.Stateless.Methods.IPersonName.GetFullName(person.Name);
personDirectory = Path.Combine(directory, Regex.Replace(personName, pattern, string.Empty), "lnk");
results.Add(new(null, personDirectory, null, string.Empty, string.Empty));
}
facesDirectory = string.Concat(dFacesContentDirectory, Path.Combine(directoryName, item.ImageFileHolder.NameWithoutExtension));
landmarksDirectory = string.Concat(d2ResultsFullGroupDirectory, Path.Combine(directoryName, item.ImageFileHolder.NameWithoutExtension));
deterministicHashCodeKey = Shared.Models.Stateless.Methods.INamed.GetDeterministicHashCodeKey(item, closest);
checkFile = Path.Combine(directory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}");
faceFileInfo = new(Path.Combine(facesDirectory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}.png"));
landmarkFileInfo = new(Path.Combine(landmarksDirectory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}.gif"));
if (string.IsNullOrEmpty(personDirectory))
shortcutFile = string.Empty;
else
shortcutFile = Path.Combine(personDirectory, $"{deterministicHashCodeKey}{item.ImageFileHolder.ExtensionLowered}.lnk");
results.Add(new(item.ResizedFileHolder, directory, faceFileInfo, checkFile, shortcutFile));
}
}
}
return results;
}
internal static void SaveClosest(string argZero, List<Container> containers, Dictionary<string, List<Person>> peopleCollection, string dFacesContentDirectory, string d2ResultsFullGroupDirectory, string eDistanceContentDirectory)
{
WindowsShortcut windowsShortcut;
List<(IFileHolder? resizedFileHolder, string directory, FileInfo? faceFileInfo, string checkFile, string shortcutFile)> collection = GetClosest(argZero, containers, peopleCollection, dFacesContentDirectory, d2ResultsFullGroupDirectory, eDistanceContentDirectory);
string[] directories = (from l in collection select l.directory).Distinct().ToArray();
foreach (string directory in directories)
{
if (string.IsNullOrEmpty(directory))
continue;
if (!Directory.Exists(directory))
_ = Directory.CreateDirectory(directory);
}
foreach ((IFileHolder? resizedFileHolder, string directory, FileInfo? faceFileInfo, string checkFile, string shortcutFile) in collection)
{
if (string.IsNullOrEmpty(directory) || string.IsNullOrEmpty(checkFile) || resizedFileHolder is null || faceFileInfo is null)
continue;
if (File.Exists(checkFile))
continue;
if (faceFileInfo.Directory is not null && faceFileInfo.Directory.Exists && faceFileInfo.Exists)
File.Copy(faceFileInfo.FullName, checkFile);
else
File.Copy(resizedFileHolder.FullName, checkFile);
}
foreach ((IFileHolder? resizedFileHolder, string directory, FileInfo? _, string checkFile, string shortcutFile) in collection)
{
if (string.IsNullOrEmpty(directory) || string.IsNullOrEmpty(checkFile) || resizedFileHolder is null)
continue;
if (string.IsNullOrEmpty(shortcutFile) || !resizedFileHolder.Exists)
continue;
try
{
windowsShortcut = new() { Path = resizedFileHolder.FullName };
windowsShortcut.Save(shortcutFile);
windowsShortcut.Dispose();
}
catch (Exception)
{ }
}
}
}